SDODV: A smart and adaptive on-demand distance vector routing protocol for MANETs

Mobile ad hoc networks (MANETS) are nodes connected in a peer-to-peer fashion. Because MANETs have challenging characteristics such as mobility and limited energy, traditional existing routing protocols are not very efficient - they suffer several limitations in terms of network stability and lifetime, especially in the emerging era of IoT, crowd-sensing, and smart cities. In this work, we present SDODV, a new smart and dynamic on-demand distance vector routing protocol for mobile ad hoc networks that addresses the shortcomings of existing routing protocols. Our proposed adaptive algorithm effectively increases the built network's lifetime by considering the network topology when establishing a route. It monitors the traffic load, nodes mobility, neighborhood density, and battery power to adjust packets accordingly. This protocol is based on the distributed reinforcement learning approach and on the traditional AODV. SDODV improves the quality of service because it chooses the shortest and most stable path while considering mobility, bandwidth, and power. Experimental results prove that SDODV outperforms the shortest path method and reduces energy consumption.